Description:

Weather and climate models continue to suffer from systematic biases, many of which are related to missing or poorly represented physical processes and deficiencies in the underlying model physics. Process-based testing and evaluation of physics are essential to identify and understand the causes of model errors and biases, and to improve the overall performance of a weather/climate model while ensuring that model adjustments or tunings can be justified on physical grounds. To advance the model physics and improve forecasting accuracy, reliability and lead times, with the ultimate goal of providing meaningful model data to drive science, inform decisions, and enrich humanity within our community and beyond, this session aims to bring together scientists who work on a variety of numerical models (such as weather/climate, regional/global, coupled/uncoupled, deterministic/ensemble, etc.).  The session will focus on: 1) testing and evaluation of model physics components, their interactions, and the impact on the overall performance of a model, and 2) using process-based testing and evaluation to advance understanding of physical processes. Abstracts that apply hierarchical testing approaches and process-based model verification and evaluation methods are particularly encouraged.